Daniel G. Aliaga
Associate Professor of Computer Science
305 N. University St.
West Lafayette, IN 47907-2066
FAX: (765) 494-0739
Email: aliaga at cs purdue edu
Short Biography: Dr. Aliaga’s research is primarily in the area of 3D computer graphics but overlaps with computer vision and visualization while also having strong multi-disciplinary collaborations outside of computer science. His research activities are divided into three groups: a) his pioneering work in the multi-disciplinary area of inverse modeling and design; b) his first-of-its-kind work in codifying information into images and surfaces, and c) his compelling work in a visual computing framework including high-quality 3D acquisition methods. Dr. Aliaga’s inverse modeling and design is particularly focused at digital city planning applications that provide innovative “what-if” design tools enabling urban stake holders from cities worldwide to automatically integrate, process, analyze, and visualize the complex interdependencies between the urban form, function, and the natural environment. Dr. Aliaga’s first computer graphics publication was in 1990 and since has resulted in cutting-edge new methodologies (e.g., 130+ refereed publications in top-venues covering multiple disciplines), membership in more than 70 program committees including all of the leading conferences in his field, several on-going international multi-disciplinary collaborations (i.e., with world experts in computer science, photogrammetry, urban planning, architecture, meteorology, atmospheric sciences, earth sciences, traffic engineering, and more), invited national and international talks and presentations (i.e., about 50 talks and presentations in United States, Brasil, Colombia, Ecuador, France, Japan, Korea, Peru, Qatar, Sweden, and Switzerland), funding support from multiple entities (e.g., NSF, IARPA, Internet2, MTC, Google, Microsoft, Adobe) and technology transfer (e.g., roles in several startups and multiple patents). Dr. Aliaga performs his research in close interaction with both PhD candidates and with undergraduate students.
o Associate Professor, Purdue University, 2010-present.
o Visiting Professor in King Abdullah University of Science and Technology, Division of Computer Science, Saudi Arabia, Fall 2018.
o Visiting Professor in Computer Vision and Geometry Group, Department of Computer Science, ETH Zurich, 2011.
o Visiting Professor in Chair for Information Architecture, Department of Architecture, ETH Zurich, 2011.
o Assistant Professor, Purdue University, 2003-2010.
o Research Staff, Princeton University, 2003.
o Member of Technical Staff, Bell Labs, 1999-2002.
o Ph.D., Computer Science, University of North Carolina at Chapel Hill, 1993-1999.
o M.S., Computer Science, University of North Carolina at Chapel Hill, 1991-1993.
o B.S. Computer Science, Magna Cum Laude, Honors, Brown University, 1987-1991.
o High School, Colegio Santa Maria, Lima - Peru, 1982-1986.
Our objective is to capture, simulate, and modify models of urban environments. Today, more than half of the world’s population of 7 billion people lives in cities – and that number is only expected to grow over the next 30 years. Cities, and urban spaces of all sizes, are however extremely complex and their modeling is still not solved. We pursue multi-disciplinary research focused on visual computing tools for improving the complex urban ecosystem and for “what-if” exploration of sustainable urban designs, including integrating urban 3D modeling, simulation, visualization, meteorology, and traffic modeling. To date, we have developed several algorithms and large-scale software systems using ground-level imagery, aerial imagery, GIS data, and forward and inverse procedural modeling to create/modify 3D and 2D urban models.
Appearance editing offers a unique way to view visually altered objects with various appearances or visualizations. By carefully controlling how an object is illuminated using digital projectors, we obtain stereoscopic imagery for any number of observers with everything visible to the naked eye (i.e., no need for head-mounts or goggles). Such ability is useful for various applications, including scientific visualization, virtual restoration of cultural heritage, and display systems.
We seek to provide methods to embed into a physical object information for a variety of purposes, including genuinity detection, tamper detection, and multiple appearance generation. Genuinity detection refers to encoding fragile or robust signatures so that a copy, or tampered, version can be differentiated from the original object. Multiple appearance generation refers to generalizing the encoded information from a signature to a different appearance of the same physical object. The project also includes the development of underlying infrastructure for 3D model acquisition and for appearance/signature creation and extraction using projector-based illumination.
We introduce a photogeometric framework for acquiring 3D objects with sub-millimeter accuracy. The defining characteristic of our framework is leveraging the complementary advantages of photometric and geometric acquisition. The two approaches are tightly integrated in an iterative acquisition process that achieves self-calibration, multi-viewpoint sampling, and high level of detail.
Conventional 3D reconstruction from digital photographs requires (pre-calibration) or computes (self-calibration) camera pose for each photograph. We have developed a mathematical framework where the parameters defining camera poses are eliminated from the nonlinear system of 3-D reconstruction equations, which leads to significantly more robust and accurate 3D models.
Structured light is a powerful approach for acquiring 3-D models of real world scenes. The scene is illuminated with a custom pattern of light and imaged with a digital camera. An important challenge in structured light acquisition comes from glossy and specular objects which reflect the patterns of light and create false positives. We have developed an iterative and adaptive algorithm that reduces the inter-reflection within the scene, which leads to robust pixel classification and to accurate and dense 3-D reconstruction.
Most 3-D acquisition systems assume that the scene is static. We have taken significant steps towards supporting the acquisition of dynamic scenes by developing algorithms that detect and leverage repetitive motion in the scene (e.g. person walking, flag waving). Our approach produces space-time 3D models using as few as two cameras or one camera-projector pair.
Obtaining image sequences of popular and active environments is often hindered by unwanted interfering occluders. In this work, we propose a family of Occlusion-Resistant Camera designs for acquiring such environments. Our cameras explicitly remove interfering occluders from acquired data in real-time, during live capture.
We present an image-based approach to providing interactive and photorealistic walkthroughs of complex indoor environments. Our strategy is to obtain a dense sampling of viewpoints in a large static environment with omnidirectional images and to replace the 3D reconstruction challenges with easier problems of motorized-cart control, dense image-based sampling, and compression.
The project investigates several graphical and educational tools using Tablet PCs. We have developed hardware and software tools for tabletop mixed-reality and for Tablet PC applications in classrooms.
A key component of providing realism is rendering large and detailed 3D models at high frame rates. We explore various rendering acceleration methods, including visibility culling, geometry simplification, and image-based rendering.
· C.D.T. Mathew, B. Benes, D. Aliaga, An output-driven approach to design a swarming model for architectural indoor environments, Computers & Graphics, Vol. 87, 103-110, 2020.
Current course: CS334 Fundamentals of Computer Graphics
Xiaowei Zhang (CS, PhD candidate)
Chris May (CS, PhD candidate)
Tharindu Mathew (CS, PhD candidate)
Zixun Xu (CS, PhD candidate)
Liu He (CS, PhD student)
David Song (CS, PhD student)
Don Baize (CS, PhD student)
Gen Nishida (CS, PhD 2018, went to GM Cruise)
Ilke Demir (CS, PhD 2016, went to Facebook)
Ignacio Garcia-Dorado (CS, PhD 2015, went to Google Research)
Alvin Law (CS, PhD 2011, went to Google)
Yi Xu (CS, PhD 2010, went to GE Research)
Daniel Bekins (CS, MS 2005, went to Electronic Arts)
Scott Yost (CS, MS 2004, went to Microsoft)
Committee member (partial list):
Paul Schmid (EAS, PhD student)
Paul Rosen (CS, PhD 2010, went to Research Asst Prof @ University of Utah)
Mihai Mudure (CS, PhD 2008, went to Google)
Huiying Xu (CS, PhD 2007, went to Cisco)
David Gotz (CS, PhD 2005, UNC, went to IBM Research)
Jerry Hsu (CS, BS 2020)
Jacob Dunbar (CS, BS 2018)
Hareesh Gali (CS, BS 2020)
Aakash Ranga (CS, BS 2019)
Ben Staiger (CS, BS 2017)
David Fifer (CS, BS 2013)
Yeong-Ouk Kim (CS, BS 2012)
John McCoy Crofts (CS, BS 2012)
Andy Feldkamp (CGT, BS 2011)
Tyler Smith (CS, BS 2011)
Philip Jarvis (CS, BS 2011)
Aaron Link (CS, BS 2009)
Robert Insley (CS, BS 2008)
Dat Nyugen, Nitin Nalreja, Nimesh Amin (CS, BS 2006)
Paul Ardis (CS, BS 2005, now at Univ. Rochester)
Jamie Gennis (CS, BS 2005, now at NVIDIA)
Jonathan Deutsch (CS, BS 2005, now at Apple Corp)
Darin Rajan (CS, BS 2005)
o NSF EAGER, (PI): Minimal 3D Modeling Methodology, 2020-2021.
o E-CAS: Building Clouds: Worldwide Building Typology Modeling from Images, 2019-2020.
o NSF IIS, (PI): Functional Proceduralization of 3D Geometric Models, 2018-2021.
o NSF OAC, (PI): U-Cube - A Cyberinfrastructure for Unified and Ubiquitous Urban Canopy Parameterization, 2018-2021.
o IARPA Core3D, (co-PI): LEGO - Large-Scale Environment-Modeling with Geometric Optimization, 2017-2021.
o NSF I/UCRC, (Co-PI): “Phase I: Robots and Sensors for the Human Well-being”, 2014-2020.
o NSF IIS, (Purdue PI): A Heterogeneous Inference Framework for 3D Modeling and Rendering of Sites, 2013-2016.
o NSF CBET, (PI): “STRONG Cities – Simulation Technologies for the Realization of Next Generation Cities”, 2012-2016.
o NSF IIS, (PI): “Integrating Behavioral, Geometrical and Graphical Modeling to Simulate and Visualize Urban Areas”, 2010-2014.
o Google Research Award, (PI): “Modeling of Buildings from Photographs”, 2011-present.
o Metropolitan Transportation Commission, (Purdue PI): “Urban Simulation Visualization”, 2011-2013.
o NSF CNS, (PI): “A Computational Framework for Marking Physical Objects against Counterfeiting and Tampering”, 2009-2013.
o NSF OCI, (co-PI): “INTEROP: Developing Community-based Drought Information Network Protocols and Tools for Multidisciplinary Regional Scale Applications (DRInet)”, 2008-2013.
o Purdue-IUPUI Applied Research Grant, (PI): “Digital Inspection and Virtual Restoration of 3D Objects”, 2008-2009.
o Adobe Inc., (Co-PI): “Vector Pattern Modeling and Editing“, 2008-present.
o PACE/Hewlett-Packard Hardware Grant, (PI): 2008.
o NSF REU, (PI): “3D Scene Digitization”, 2006-2008.
o NSF MSPA-MCS, (PI): “3D Scene Digitization: A Novel Invariant Approach for Large-Scale Environment Capture”, 2004-2008.
o Microsoft Research, (PI): “PMR: Portable Mixed Reality”, 2005-present.
o Microsoft Research, (PI): “MRT: A Mixed Reality Tabletop”, 2004-present.
o Discovery Park Faculty Research Fellow (2013-2014)
o Purdue University Diversity Award (2012)
o OECD Fellowship Recipient (2011)
o “Holistic 3D Urban Modeling”, Invited Talk, ECCV Workshop on Holistic Modeling, August, 2020.
o “Urban Scene Generation”, Invited Talk, CVPR Workshop on Learning 3D Generative Models, June, 2020.
o “3D City Generation for Machine Learning and Urban Design”, Invited Talk, CVPR Workshop on 3D Scene Generation, June, 2019.
o “STRONG Cities: Simulation Technologies for the Realization of Next Generation Cities”, Colloquium, King Abdullah University of Science and Technology (KAUST), Saudi Arabia, 2018.
o “Interactively Designing Future Buildings and Cities”, Keynote, International Workshop on Visual Computing, Bogota, Colombia, 2018.
o “Cities of Tomorrow: Visual Computing for Designing and Modeling Urban Ecosystems”, Keynote, Peruvian Symposium On Computer Graphics And Imaging, Arequipa, Peru, 2017.
o “Cities of Tomorrow: Visual Computing for Designing and Modeling Urban Ecosystems”, Invited Speaker, Universidad de Tecnologia y Ciencias, Lima, Peru, 2017
o “Designing and Modeling Cities of Tomorrow”, Invited Talk, Bogota ACM SIGGRAPH, Bogota, Colombia, 2016.
o “Designing and Modeling Cities of Tomorrow”, Invited Talk, SIBGRAPI, Brasil, Sao Jose, 2016.
o “Cities of Tomorrow”, Seminar, INRIA – Sophia, Antipolis, France, July 2015.
o “Appearance Editing”, Seminar, INRIA – Sophia, Antipolis, France, July 2015.
o “Designing and Modeling Intelligent Cities”, Invited Talk, Universidad de Ingenieria y Tecnologia, Lima, Peru, July, 2013.
o “Cities of Tomorrow: Visual Computing for Sustainable Urban Ecosystems”, Invited Talk, National Institute of Informatics, Tokyo, Japan, July 2013.
o “Cities of Tomorrow: Visual Computing for Sustainable Urban Ecosystems”, Invited Talk, Networks and Complex Systems at IU Bloomington, Cyberinfrastructure for Network Science Center, April, 2013.
o “Appearance Editing: What you see is not what you have”, Invited Talk, 3rd Annual SIGGRAPH Chapter Conference, Bogota, Colombia, October, 2012.
o “Appearance Editing”, Invited Talk, UMIACS, Univ. of Maryland at College Park, July 2012.
o “Cities of Tomorrow: Visual Computing for Designing Sustainable Urban Ecosystems”, Keynote, National Socio-Environmental Synthesis Center (SESYNC) Workshop: Visualization Technologies to Support Research on Human-Environmental Interactions, July, 2012.
o “Appearance Editing”, Invited Talk, ETH Computer Science/Disney Research Lab, Zurich, Switzerland, November, 2011.
o “Future City Systems”, Invited Panel Member and Presenter, Asia-Pacific Conference on Systems Engineering (APCOSE): Green Growth and Systems Engineering, October, 2011.
o “Computational Cities: Geometrical Modeling for Urban Design and Simulation”, Invited Talk, Center for Image Analysis, Uppsala University, Sweden, September, 2011.
o “Computational Cities: Geometrical Modeling for Urban Design and Simulation”, Invited Talk, Department of Urban Systems Engineering, Technical University of Compiegne, Compiegne, France, June, 2011.
o “Computational Cities: Geometrical Modeling for Urban Design and Simulation”, Invited Talk, Qatar Energy and Environment Institute and Qatar Computing Research Institute, Qatar Foundation, Doha, Qatar, April, 2011.
o “3D Urban Modeling and Simulation”, Guest Lecture, Chair of Information Architecture, ETH, Zurich, Switzerland, April, 2011.
o “Computational Cities: Geometrical Modeling for Urban Design and Simulation”, Guest Lecture, Chair of Computer Aided Architectural Design, ETH, Zurich, Switzerland, March, 2011.
o “Computational Cities: Geometrical Modeling for Urban Design and Simulation”, Colloquium Talk, Department of Informatics, University of Zurich, Zurich, Switzerland, March, 2011.
o AAAI Conference on Artificial Intelligence, 2021
o Eurographics, 2021
o SIBGRAPI Conference on Graphics, Patterns, and Images, 2020
o European Conference on Computer Vision, 2020
o AAAI Conference on Artificial Intelligence, 2020
o Deep Learning for Geometric Computing Workshop (at IEEE CVPR), 2020
o IEEE International Conference on Computer Vision, 2020
o Eurographics, 2020
o ACM SIGGRAPH Asia Courses, 2019
o IEEE International Conference on Computer Vision 2019
o IEEE Computer Vision and Pattern Recognition, 2019
o IEEE International Conference on Computer Vision, 2019
o British Machine Vision Conference, 2019
o SIBGRAPI, 2019
o IEEE Computer Vision and Pattern Recognition, 2018
o ACM SIGGRAPH Asia, 2017
o Eurographics, 2017
o ACM SIGGRAPH Asia, 2016
o ACM SIGGRAPH Asia Technical Briefs and Posters, 2016
o SIBGRAPI, 2016 (Program Co-Chair)
o Eurographics, 2016
o Bogota ACM SIGGRAPH, 2016 (Steering Committee)
o International Workshop on Smart Cities and Urban Analytics, 2015
o ACM SIGGRAPH, 2015
o 3DV (3D Imaging, Modeling, Processing, Visualization & Transmission), 2015
o CEIG (Congreso Espanol de Informatica Grafica), 2015
o Hobbies: vintage computers, woodworking, vintage cars, model trains, martial arts, mountain biking
o Languages: English, Spanish, some German